IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v10y2021i3p246-d508182.html
   My bibliography  Save this article

Agricultural Technical Efficiency of Smallholder Farmers in Ethiopia: A Stochastic Frontier Approach

Author

Listed:
  • Markose Chekol Zewdie

    (Department of Engineering Management, Faculty of Business and Economics, University of Antwerp, Stadscampus, Prinsstraat 13, 2000 Antwerp, Belgium
    Department of Economics, Peda Campus, College of Business and Economics, Bahir Dar University, Bahir Dar P.O. Box 79, Ethiopia)

  • Michele Moretti

    (Department of Engineering Management, Faculty of Business and Economics, University of Antwerp, Stadscampus, Prinsstraat 13, 2000 Antwerp, Belgium
    Department of Agriculture, Food and Environment, University of Pisa, via del Borghetto 80, 56124 Pisa, Italy)

  • Daregot Berihun Tenessa

    (Department of Economics, Peda Campus, College of Business and Economics, Bahir Dar University, Bahir Dar P.O. Box 79, Ethiopia)

  • Zemen Ayalew Ayele

    (Department of Agricultural Economics, Zenzelima Campus, Bahir Dar University, Bahir Dar P.O. Box 79, Ethiopia)

  • Jan Nyssen

    (Department of Geography, Ghent University, Krijgslaan 281, S8, 9000 Gent, Belgium)

  • Enyew Adgo Tsegaye

    (Department of Natural Resource Management, Zenzelima Campus, Bahir Dar University, Bahir Dar P.O. Box 79, Ethiopia)

  • Amare Sewnet Minale

    (Department of Geography and Environmental Studies, Peda Campus, Bahir Dar University, Bahir Dar P.O. Box 79, Ethiopia)

  • Steven Van Passel

    (Department of Engineering Management, Faculty of Business and Economics, University of Antwerp, Stadscampus, Prinsstraat 13, 2000 Antwerp, Belgium
    Department of Economics, Peda Campus, College of Business and Economics, Bahir Dar University, Bahir Dar P.O. Box 79, Ethiopia)

Abstract

In the past decade, to improve crop production and productivity, Ethiopia has embarked on an ambitious irrigation farming expansion program and has introduced new large- and small-scale irrigation initiatives. However, in Ethiopia, poverty remains a challenge, and crop productivity per unit area of land is very low. Literature on the technical efficiency (TE) of large-scale and small-scale irrigation user farmers as compared to the non-user farmers in Ethiopia is also limited. Investigating smallholder farmers’ TE level and its principal determinants is very important to increase crop production and productivity and to improve smallholder farmers’ livelihood and food security. Using 1026 household-level cross-section data, this study adopts a technology flexible stochastic frontier approach to examine agricultural TE of large-scale irrigation users, small-scale irrigation users and non-user farmers in Ethiopia. The results indicate that, due to poor extension services and old-style agronomic practices, the mean TE of farmers is very low (44.33%), implying that there is a wider room for increasing crop production in the study areas through increasing the TE of smallholder farmers without additional investment in novel agricultural technologies. Results also show that large-scale irrigation user farmers (21.05%) are less technically efficient than small-scale irrigation user farmers (60.29%). However, improving irrigation infrastructure shifts the frontier up and has a positive impact on smallholder farmers’ output.

Suggested Citation

  • Markose Chekol Zewdie & Michele Moretti & Daregot Berihun Tenessa & Zemen Ayalew Ayele & Jan Nyssen & Enyew Adgo Tsegaye & Amare Sewnet Minale & Steven Van Passel, 2021. "Agricultural Technical Efficiency of Smallholder Farmers in Ethiopia: A Stochastic Frontier Approach," Land, MDPI, vol. 10(3), pages 1-17, March.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:3:p:246-:d:508182
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/10/3/246/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/10/3/246/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Thomas P. Triebs & David S. Saal & Pablo Arocena & Subal C. Kumbhakar, 2016. "Estimating economies of scale and scope with flexible technology," Journal of Productivity Analysis, Springer, vol. 45(2), pages 173-186, April.
    2. Subal C. Kumbhakar & Hung-Jen Wang, 2015. "Estimation of Technical Inefficiency in Production Frontier Models Using Cross-Sectional Data," Springer Books, in: Subhash C. Ray & Subal C. Kumbhakar & Pami Dua (ed.), Benchmarking for Performance Evaluation, edition 127, chapter 0, pages 1-73, Springer.
    3. Kees Jan Van Garderen & Chandra Shah, 2002. "Exact interpretation of dummy variables in semilogarithmic equations," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 149-159, June.
    4. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107609464, January.
    5. Fitsum Assefa Adela & Joachim Aurbacher & Gumataw Kifle Abebe, 2019. "Small-scale irrigation scheme governance - poverty nexus: evidence from Ethiopia," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 11(4), pages 897-913, August.
    6. Bravo-Ureta, Boris E. & Higgins, Daniel & Arslan, Aslihan, 2020. "Irrigation infrastructure and farm productivity in the Philippines: A stochastic Meta-Frontier analysis," World Development, Elsevier, vol. 135(C).
    7. Andre Croppenstedt & Mulat Demeke, 1997. "An empirical study of cereal crop production and technical efficiency of private farmers in Ethiopia: a mixed fixed-random coefficients approach," Applied Economics, Taylor & Francis Journals, vol. 29(9), pages 1217-1226.
    8. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    9. Gebrehiwot, Kidanemariam G. & Makina, Daniel & Woldu, Thomas, 2017. "The impact of micro-irrigation on households’ welfare in the northern part of Ethiopia: an endogenous switching regression approach," Studies in Agricultural Economics, Research Institute for Agricultural Economics, vol. 119(3), December.
    10. Anbes Tenaye, 2020. "Technical Efficiency of Smallholder Agriculture in Developing Countries: The Case of Ethiopia," Economies, MDPI, vol. 8(2), pages 1-27, April.
    11. Abdul-Rahaman, Awal & Abdulai, Awudu, 2018. "Do farmer groups impact on farm yield and efficiency of smallholder farmers? Evidence from rice farmers in northern Ghana," Food Policy, Elsevier, vol. 81(C), pages 95-105.
    12. Coelli, Tim & Fleming, Euan, 2004. "Diversification economies and specialisation efficiencies in a mixed food and coffee smallholder farming system in Papua New Guinea," Agricultural Economics, Blackwell, vol. 31(2-3), pages 229-239, December.
    13. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    14. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-111, January.
    15. Dorosh, Paul A. & Rashid, Shahidur, 2013. "Food and agriculture in Ethiopia: Progress and policy challenges," Issue briefs 74, International Food Policy Research Institute (IFPRI).
    16. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    17. Seyoum, E. T. & Battese, G. E. & Fleming, E. M., 1998. "Technical efficiency and productivity of maize producers in eastern Ethiopia: a study of farmers within and outside the Sasakawa-Global 2000 project," Agricultural Economics, Blackwell, vol. 19(3), pages 341-348, December.
    18. Zewdie, Markose Chekol & Van Passel, Steven & Moretti, Michele & Annys, Sofie & Tenessa, Daregot Berihun & Ayele, Zemen Ayalew & Tsegaye, Enyew Adgo & Cools, Jan & Minale, Amare Sewnet & Nyssen, Jan, 2020. "Pathways how irrigation water affects crop revenue of smallholder farmers in northwest Ethiopia: A mixed approach," Agricultural Water Management, Elsevier, vol. 233(C).
    19. H.E.T. Holgersson & L. Nordstr�m & Ö. Öner, 2014. "Dummy variables vs. category-wise models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(2), pages 233-241, February.
    20. Hung-Jen Wang, 2002. "Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 18(3), pages 241-253, November.
    21. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    22. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    23. Akridge, Jay T. & Hertel, Thomas W., 1992. "Cooperative and Investor-Oriented Firm Efficiency: A Multiproduct Analysis," Journal of Agricultural Cooperation, National Council of Farmer Cooperatives, vol. 7, pages 1-14.
    24. Consuelo Varela‐Ortega & José M. Sumpsi & Alberto Garrido & María Blanco & Eva Iglesias, 1998. "Water pricing policies, public decision making and farmers' response: implications for water policy," Agricultural Economics, International Association of Agricultural Economists, vol. 19(1-2), pages 193-202, September.
    25. Jan Schepers, 2016. "On regression modelling with dummy variables versus separate regressions per group: Comment on Holgersson et al," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(4), pages 674-681, March.
    26. Nelson Mango & Clifton Makate & Lulseged Tamene & Powell Mponela & Gift Ndengu, 2018. "Adoption of Small-Scale Irrigation Farming as a Climate-Smart Agriculture Practice and Its Influence on Household Income in the Chinyanja Triangle, Southern Africa," Land, MDPI, vol. 7(2), pages 1-19, April.
    27. Hadri, Kaddour, 1999. "Estimation of a Doubly Heteroscedastic Stochastic Frontier Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 359-363, July.
    28. Varela-Ortega, Consuelo & M. Sumpsi, Jose & Garrido, Alberto & Blanco, Maria & Iglesias, Eva, 1998. "Water pricing policies, public decision making and farmers' response: implications for water policy," Agricultural Economics, Blackwell, vol. 19(1-2), pages 193-202, September.
    29. Hamed Taherdoost, 2016. "Sampling Methods in Research Methodology; How to Choose a Sampling Technique for Research," Post-Print hal-02546796, HAL.
    30. Jules Ngango & Seung Gyu Kim, 2019. "Assessment of Technical Efficiency and Its Potential Determinants among Small-Scale Coffee Farmers in Rwanda," Agriculture, MDPI, vol. 9(7), pages 1-12, July.
    31. E.T. Seyoum & G.E. Battese & E.M. Fleming, 1998. "Technical efficiency and productivity of maize producers in eastern Ethiopia: a study of farmers within and outside the Sasakawa‐Global 2000 project," Agricultural Economics, International Association of Agricultural Economists, vol. 19(3), pages 341-348, December.
    32. Ngango, Jules & Lee, Jungmyung & Kim, Seung Gyu, 2019. "Determinants of technical efficiency among small-scale coffee farmers in Rwanda," 2019 Annual Meeting, July 21-23, Atlanta, Georgia 291139, Agricultural and Applied Economics Association.
    33. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    34. Tafesse W. Gezahegn & Steven Van Passel & Tekeste Berhanu & Marijke D’haese & Miet Maertens, 2020. "Do bottom-up and independent agricultural cooperatives really perform better? Insights from a technical efficiency analysis in Ethiopia," Agrekon, Taylor & Francis Journals, vol. 59(1), pages 93-109, January.
    35. Zewdie, Markose Chekol & Van Passel, Steven & Cools, Jan & Tenessa, Daregot Berihun & Ayele, Zemen Ayalew & Tsegaye, Enyew Adgo & Minale, Amare Sewnet & Nyssen, Jan, 2019. "Direct and indirect effect of irrigation water availability on crop revenue in northwest Ethiopia: A structural equation model," Agricultural Water Management, Elsevier, vol. 220(C), pages 27-35.
    36. Abdulai Adams & Bedru Balana & Nicole Lefore, 2020. "Efficiency of Small-scale Irrigation Farmers in Northern Ghana: A Data Envelopment Analysis Approach," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 14(3), pages 332-352, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ming Chang & Jing Liu & Hongxu Shi & Tianfeng Guo, 2022. "The Effect of Off-Farm Employment on Agricultural Production Efficiency: Micro Evidence in China," Sustainability, MDPI, vol. 14(6), pages 1-12, March.
    2. Fang Song & Xuerong Xu, 2023. "How Operation Scale Improve the Production Technical Efficiency of Grape Growers? An Empirical Evidence of Novel Panel Methods for China’s Survey Data," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    3. Xiuqing Zou & Meihui Xie & Zhiyuan Li & Kaifeng Duan, 2022. "Spatial Spillover Effect of Rural Labor Transfer on the Eco-Efficiency of Cultivated Land Use: Evidence from China," IJERPH, MDPI, vol. 19(15), pages 1-17, August.
    4. Liangzhen Zang & Yahua Wang & Yiqing Su, 2021. "Does Farmland Scale Management Promote Rural Collective Action? An Empirical Study of Canal Irrigation Systems in China," Land, MDPI, vol. 10(11), pages 1-25, November.
    5. Shi, Hongxu & Xu, Hao & Gao, Wei & Zhang, Jinhao & Chang, Ming, 2022. "The impact of energy poverty on agricultural productivity: The case of China," Energy Policy, Elsevier, vol. 167(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ali M. Oumer & Amin Mugera & Michael Burton & Atakelty Hailu, 2022. "Technical efficiency and firm heterogeneity in stochastic frontier models: application to smallholder maize farms in Ethiopia," Journal of Productivity Analysis, Springer, vol. 57(2), pages 213-241, April.
    2. Tiziana Laureti, 2008. "Modelling Exogenous Variables in Human Capital Formation through a Heteroscedastic Stochastic Frontier," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 14(1), pages 76-89, February.
    3. repec:kap:iaecre:v:14:y:2008:i:1:p:76-89 is not listed on IDEAS
    4. Satya Paul & Sriram Shankar, 2020. "Estimating efficiency effects in a panel data stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 53(2), pages 163-180, April.
    5. Narangerel Ganbold & Shah Fahad & Hua Li & Tumendemberel Gungaa, 2022. "An evaluation of subsidy policy impacts, transient and persistent technical efficiency: A case of Mongolia," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(7), pages 9223-9242, July.
    6. Jorge Galán & Helena Veiga & Michael Wiper, 2014. "Bayesian estimation of inefficiency heterogeneity in stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 42(1), pages 85-101, August.
    7. Efecan, Volkan & Temiz, İzzettin, 2023. "Assessing the technical efficiency of container ports based on a non-monotonic inefficiency effects model," Utilities Policy, Elsevier, vol. 81(C).
    8. Paul, Satya & Shankar, Sriram, 2018. "On estimating efficiency effects in a stochastic frontier model," European Journal of Operational Research, Elsevier, vol. 271(2), pages 769-774.
    9. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    10. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    11. Paul, Satya & Shankar, Sriram, 2018. "Modelling Efficiency Effects in a True Fixed Effects Stochastic Frontier," MPRA Paper 87437, University Library of Munich, Germany.
    12. Ajayi, Victor & Weyman-Jones, Tom, 2021. "State-level electricity generation efficiency: Do restructuring and regulatory institutions matter in the US?," Energy Economics, Elsevier, vol. 104(C).
    13. Dipanwita Sarkar & Trevor C. Collier, 2019. "Does host-country education mitigate immigrant inefficiency? Evidence from earnings of Australian university graduates," Empirical Economics, Springer, vol. 56(1), pages 81-106, January.
    14. Luigi Brighi & Paolo Silvestri, 2019. "Inefficiency in Childcare Production: Evidence from Italian Microdata," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 5(1), pages 103-133, March.
    15. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    16. Subal Kumbhakar & Gudbrand Lien & J. Hardaker, 2014. "Technical efficiency in competing panel data models: a study of Norwegian grain farming," Journal of Productivity Analysis, Springer, vol. 41(2), pages 321-337, April.
    17. Christopher F. Parmeter & Hung-Jen Wang & Subal C. Kumbhakar, 2017. "Nonparametric estimation of the determinants of inefficiency," Journal of Productivity Analysis, Springer, vol. 47(3), pages 205-221, June.
    18. Getu Hailu & B. James Deaton, 2016. "Agglomeration Effects in Ontario’s Dairy Farming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(4), pages 1055-1073.
    19. Federico Belotti & Silvio Daidone & Giuseppe Ilardi & Vincenzo Atella, 2013. "Stochastic frontier analysis using Stata," Stata Journal, StataCorp LP, vol. 13(4), pages 718-758, December.
    20. Giovanni Marin & Alessandro Palma, 2015. "Technology invention and diffusion in residential energy consumption. A stochastic frontier approach," IEFE Working Papers 81, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    21. Fabio Pieri & Enrico Zaninotto, 2013. "Vertical integration and efficiency: an application to the Italian machine tool industry," Small Business Economics, Springer, vol. 40(2), pages 397-416, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:10:y:2021:i:3:p:246-:d:508182. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.